Search Results for author:
Found 15 papers, 1 papers with code
CBIDR: A novel method for information retrieval combining image and data by means of TOPSIS applied to medical diagnosis
The goal is to aid medical professionals in their final diagnosis by retrieving images and clinical data of patient that are most similar to query data from the database.
Skin cancer diagnosis using NIR spectroscopy data of skin lesions in vivo using machine learning algorithms
The obtained results indicate the first steps in CAD of skin lesions aiming the automated triage of patients with skin lesions in vivo using NIR spectral data.
Bayesian artificial brain with ChatGPT
In this paper, we present the same set of 10 Bayesian reasoning problems to ChatGPT.
Development of a hybrid method for stock trading based on TOPSIS, EMD and ELM
Deciding when to buy or sell a stock is not an easy task because the market is hard to predict, being influenced by political and economic factors.
Exploring Advances in Transformers and CNN for Skin Lesion Diagnosis on Small Datasets
Skin cancer is one of the most common types of cancer in the world.
Solving integer multi-objective optimization problems using TOPSIS, Differential Evolution and Tabu Search
This paper presents a method to solve non-linear integer multiobjective optimization problems.
Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data
Due to the difficulty and subjectivity in the clinical diagnosis of skin lesions, Computer-Aided Diagnosis systems are being developed for assist experts to perform more reliable diagnosis.
A Smartphone based Application for Skin Cancer Classification Using Deep Learning with Clinical Images and Lesion Information
In this work, we present a smartphone-based application to assist on skin cancer detection.
Discovering an Aid Policy to Minimize Student Evasion Using Offline Reinforcement Learning
High dropout rates in tertiary education expose a lack of efficiency that causes frustration of expectations and financial waste.
Recent advances in deep learning applied to skin cancer detection
Skin cancer is a major public health problem around the world.
The impact of patient clinical information on automated skin cancer detection
These models are applied to the presented dataset using only the images and combining them with the patient clinical information.
A smartphone application to detection and classification of coffee leaf miner and coffee leaf rust
In the segmentation of foliar damages, the Otsu algorithm and the iterative threshold algorithm, in the YCgCr color space, have been used and compared to k-means.
Application of Genetic Algorithms to the Multiple Team Formation Problem
Allocating of people in multiple projects is an important issue considering the efficiency of groups from the point of view of social interaction.
Ranking of classification algorithms in terms of mean-standard deviation using A-TOPSIS
In machine learning it is common run the algorithms several times and then a statistic is calculated in terms of means and standard deviations.
An approach to dealing with missing values in heterogeneous data using k-nearest neighbors
Techniques such as clusterization, neural networks and decision making usually rely on algorithms that are not well suited to deal with missing values.
